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Iambackup/gemma-2-2b-it-abliterated-GGUF

Iambackup Gemma 2B GGUF second-order 8K ctx
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Response includes
  • classification m8
  • files 17
  • benchmarks 16 entries
  • hub_downloads_all_time 1,245
  • author_summary 36 models
  • readme_text full
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Abliteration classifier · v1.0.0
M8
Primary method

Repackaging (quantization)

Applied on top of direct removal inherited from the base model.
Confidence
MEDIUM
Inherited from base model
Why this label 3 signals
Method inferred from partial signals - repository name, related files, or tag patterns. Producer identity not confirmed; label may sharpen or shift as we gather more evidence.
  • 'abliterated' in name/tags
  • is_gguf=1
  • assume M1 (base ablation) + M8 (GGUF quant) - default when producer unknown
Refusal direction extraction

No specific extraction method could be identified for this model. The producer either did not document it or used a proprietary pipeline.

What is a refusal direction? →
Downloads · lifetime
1K
221 last 30d - stable
Likes
0
Model age
4mo ago
created 2026-06-12
Downloads over time
Now1.3K→from0↑0%
04679341.4K0 on Jun 101.3K on Oct 11JunJulAugSepOct
Jun 10 → Oct 11 · 57 snapshots · spans 123 days

Benchmarks

Benchmark Score Source
BBH average 0.38292904397457517 OpenLLM-v2
IFEval instruct 0.5911270983213429 OpenLLM-v2
IFEval-Prompt 0.47504621072088726 OpenLLM-v2
MATH lvl 5 0.0015105740181268882 OpenLLM-v2
MMLU-Pro 0.25382313829787234 OpenLLM-v2
Entertainment 1.2 UGI
Hazardous 1.8 UGI
Natural Intelligence 11.25 UGI
Political lean -27.7% UGI
Sensitive-Info 11.98 UGI
SocPol 0.8 UGI
UGI 29.65 UGI
Willingness (10) 6.5 UGI
W10-Adherence 7 UGI
W10-Direct 6 UGI
Writing 24.68 UGI

Genealogy 0 direct forks

Full fork graph →

This model's place in the market. Above: what it was derived from. Below: the tree of everything derived from it.

Metadata

License
gemma
Languages
en
Quantizations
F16 IQ3 IQ4 Q2_K Q3_K Q4_K Q5_K Q6_K Q8_0
Tags
transformers gguf en base_model:IlyaGusev/gemma-2-2b-it-abliterated base_model:quantized:IlyaGusev/gemma-2-2b-it-abliterated license:gemma endpoints_compatible region:us conversational

Related

Total size
26.6 GB
Files
17
Quantizations
10
Registered
2026-08-22 13:56
Last updated on HF
2026-06-12 17:20

Files by quantization

F16 1 file 4.88 GB
gemma-2-2b-it-abliterated.f16.gguf 4.88 GB e32279bf download
Q8_0 1 file 2.59 GB
gemma-2-2b-it-abliterated.Q8_0.gguf 2.59 GB dda0f9e5 download
Q6_K 1 file 2.00 GB
gemma-2-2b-it-abliterated.Q6_K.gguf 2.00 GB 6e472abe download
Q5_K 2 files 3.54 GB
gemma-2-2b-it-abliterated.Q5_K_M.gguf 1.79 GB 077f177b download
gemma-2-2b-it-abliterated.Q5_K_S.gguf 1.75 GB 32d5c2bb download
Q4_K 2 files 3.12 GB
gemma-2-2b-it-abliterated.Q4_K_M.gguf 1.59 GB e54a967e download
gemma-2-2b-it-abliterated.Q4_K_S.gguf 1.53 GB 054a9caa download
IQ4 1 file 1.47 GB
gemma-2-2b-it-abliterated.IQ4_XS.gguf 1.47 GB 0c742fb3 download
Q3_K 3 files 4.07 GB
gemma-2-2b-it-abliterated.Q3_K_L.gguf 1.44 GB cb28b585 download
gemma-2-2b-it-abliterated.Q3_K_M.gguf 1.36 GB ccfe7a4d download
gemma-2-2b-it-abliterated.Q3_K_S.gguf 1.27 GB 7512d4c9 download
IQ3 3 files 3.79 GB
gemma-2-2b-it-abliterated.IQ3_M.gguf 1.30 GB f711e8dd download
gemma-2-2b-it-abliterated.IQ3_S.gguf 1.27 GB 77955cfb download
gemma-2-2b-it-abliterated.IQ3_XS.gguf 1.22 GB 4cfa03e1 download
Q2_K 1 file 1.15 GB
gemma-2-2b-it-abliterated.Q2_K.gguf 1.15 GB bd8f5113 download
Auxiliary files 2 files 6.47 KB
README.md 3.91 KB cddde61b download
.gitattributes 2.56 KB 0fa4e846 download

README current version from Hugging Face


base_model: IlyaGusev/gemma-2-2b-it-abliterated
language:

  • en
    library_name: transformers
    license: gemma
    quantized_by: mradermacher

About

static quants of https://huggingface.co/IlyaGusev/gemma-2-2b-it-abliterated

weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.

Usage

If you are unsure how to use GGUF files, refer to one of TheBloke's
READMEs
for
more details, including on how to concatenate multi-part files.

Provided Quants

(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)

Link Type Size/GB Notes
GGUF Q2_K 1.3
GGUF IQ3_XS 1.4
GGUF IQ3_S 1.5 beats Q3_K*
GGUF Q3_K_S 1.5
GGUF IQ3_M 1.5
GGUF Q3_K_M 1.6 lower quality
GGUF Q3_K_L 1.7
GGUF IQ4_XS 1.7
GGUF Q4_K_S 1.7 fast, recommended
GGUF Q4_K_M 1.8 fast, recommended
GGUF Q5_K_S 2.0
GGUF Q5_K_M 2.0
GGUF Q6_K 2.3 very good quality
GGUF Q8_0 2.9 fast, best quality
GGUF f16 5.3 16 bpw, overkill

Here is a handy graph by ikawrakow comparing some lower-quality quant
types (lower is better):

image.png

And here are Artefact2's thoughts on the matter:
https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9

FAQ / Model Request

See https://huggingface.co/mradermacher/model_requests for some answers to
questions you might have and/or if you want some other model quantized.

Thanks

I thank my company, nethype GmbH, for letting
me use its servers and providing upgrades to my workstation to enable
this work in my free time.

README history 1 version

The author's README evolved over time. Click a version to see its content at that point.

  1. 2026-06-12Duplicate from mradermacher/gemma-2-2b-it-abliterated-GGUFa7596373.9 KB
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